The present invention relates to a system for the reliable estimation of unknown information regarding railroad freight vehicles in transit.
A railroad track network exists throughout North America, upon which railroad freight traffic flows. This railroad track network, though owned by a comparatively small number of entities, e.g., Union Pacific, Burlington Northern Santa Fe, etc., is shared by a vast number of railroad freight carriers. In addition, many businesses neither own the railroad track, nor engage in hauling freight across it, but instead merely own specific equipment such as railroad cars, ocean containers and other intermodal equipment, etc., that is used by railroad freight carriers on a rental basis. Furthermore, to facilitate the most efficient use of the finite railroad track network, individual units of railroad equipment are shared among all freight carriers according to standardized use and compensation rules promulgated by RailInc., a wholly owned subsidiary of the Association of American Railroads. That is to say, when a particular railcar arrives at a destination and is unloaded of its cargo, it may then be made available to another freight carrier, loaded with new cargo, and thereafter depart for a new destination.
In order to most efficiently manage a system that shares both railroad track and railroad equipment, a standardized informational database is necessary to identify individual railroad freight equipment, track their respective movements, assign available equipment to freight carriers, and account for the value of using particular equipment. As one example, if a railroad freight carrier is expecting 500 ocean containers to arrive at a port, at a particular future date, for rail transport elsewhere, sufficient railroad cars will need to be assigned to it on that date and at that location. If it were possible to identify rail cars already in transit, but whose destination for unloading its cargo was either at the needed location or sufficiently close to the needed location, and whose estimated time of arrival is sufficiently close to the time needed, then few, if any, rail cars would have to remain empty for a significant period of time just to meet the anticipated needs of that freight carrier. Thus, as can readily be seen, the use of the railroad track network will be more efficient as the detail and accuracy of such an informational database increases. Early efforts at developing a standardized database of railroad equipment were relatively simple. In the late 1960s, the Association of American Railroads (AAR) developed a crude optical identification system, called Automatic Car Identification (ACI), in which mandatory color-coded labels were mounted to the side of individual rail cars and other railroad equipment. Due to several factors, however, including deterioration and obfuscation of the labels by dust etc., the system's accuracy was very low, and was abandoned in the 1970s.
In the mid-1980s, Burlington Northern developed a prototype informational database of railroad freight equipment that was patterned after similar systems then used by various maritime shipping companies. Specifically, the prototype database utilized radio transponders mounted to freight equipment to broadcast a signal comprising a unique identifier for the respective equipment to which the transponder was mounted. These signals were then read by wayside reader sites positioned adjacent a railroad track at selected intervals. This prototype system proved to be virtually 100% effective at relaying the identification code of a railcar or other equipment passing a reader site.
Based on these results, the Association of American Railroads wrote an Automatic Equipment Identification (AEI) standard for the North American rail industry that produced a transponder/reader specification including a data format for an identification tag to singularly identify of a piece of railroad equipment. This standard was later made mandatory, and by 1994 all 1.4 million rail cars in North American interchange service were to be tagged in accordance with the standard adopted. Over 3,000 readers have been installed by the railways in North America as of the Dec. 31, 2000.
In practice, as a rail car passes an AEI reader, the RF transponder broadcasts a signal comprising a time stamp, an identification code for the rail car, and an identification code for the AEI reader. These signals, called car location messages (CLM) are then relayed to a central database for data processing to hack the physical location of rail cars on the railroad track network.
In the years since the adoption of the AEI standard, relatively sophisticated techniques have been developed to analyze the CLM data received from the respective transponders of railroad equipment in transport across the North American railroad network. For example, virtually all embarkation and destination locations include AEI readers that record the departure and arrival time of railroad equipment. Over time, the CLM data received from the departure and arrival points, along with CLM data received from intermediate AEI readers enroute have been used to develop increasingly accurate statistical relationships between pairs of AEI readers. For example, where a system has stored a statistically significant number of previous CLM readings of individual units of rail car equipment at a particular embarkation AEI reader, all having arrived at another particular destination with its own AEI reader, the average time of arrival at the destination from the embarkation point, and other statistical measures are contemporaneously computed as a next unit of railcar equipment sends a CLM message as it departs en-route to that destination, so that an estimated time of arrival (ETA), along with a numerical confidence measure of that arrival time (e.g., variance or standard deviations), are computed. Moreover, as the railcar passes other AEI readers en-route, this ETA and its associated confidence are updated from the statistical data relating rail car traffic between that intermediate AEI reader and the AEI reader at the destination.
As can easily be appreciated, the AEI specification thus enables planners to efficiently assign rail cars to freight carriers for particular transportation requirements, by using the foregoing ETA computations, along with other appropriate statistical measures.
This is not to say, however, that the existing system is either perfectly efficient or anywhere near so. One of the primary inefficiencies results from a combination of the sparseness of AEI readers along many routes, along with the number of intervening junctions, etc. between AEI readers. For example, it is not uncommon for several hundreds of miles to elapse between CLM messages from AEI readers along specific routes, particularly in the western portions of the United States and Canada. Between these AEI readers are many potential junctions, enabling multiple different paths to a single destination from any given AEI reader. Thus, even where a statistically significant number of prior instances of travel between a given AEI reader and a given destination may produce an average (or estimated) time of arrival, the spread or deviation about that average may be significant, translating to a low confidence in that ETA. Moreover, even in areas where AEI readers are dense, i.e., near major cities like Chicago, these areas typically experience a higher than average chance of backlogs where rail cars simply sit on a track waiting for the route ahead to become available. This, also, tends to increase the variance about the average historical arrival time, frustrating somewhat the ability to plan on the basis of the estimated arrival times provided. Thus, while the ability to use historical statistical interrelationships between two arbitrary AEI readers greatly assists the efficient use of a shared railroad network, there nonetheless still exists a large amount of inefficiency, minimization of which would be desirable.
The foregoing and other objectives, features, and advantages of the invention will be more readily understood upon consideration of the following detailed description of the invention taken in conjunction with the accompanying drawings.